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Research Papers

SMR Fuel Cycle Optimization Using LWROpt

[+] Author and Article Information
Keith E. Ottinger

University of Tennessee,
Department of Nuclear Engineering,
Pasqua Engineering Building, Knoxville, TN 37996-2300
e-mail: kottinge@utk.edu

G. Ivan Maldonado

University of Tennessee,
Department of Nuclear Engineering,
Pasqua Engineering Building, Knoxville, TN 37996-2300
e-mail: ivan@utk.edu

Manuscript received May 6, 2016; final manuscript received August 16, 2016; published online December 20, 2016. Assoc. Editor: Akos Horvath.

ASME J of Nuclear Rad Sci 3(1), 011014 (Dec 20, 2016) (8 pages) Paper No: NERS-16-1047; doi: 10.1115/1.4034573 History: Received May 06, 2016; Accepted August 16, 2016

This article describes the light water reactor optimizer (LWROpt), a fuel cycle optimization code originally developed for BWRs, which has been adapted to perform core fuel reload and/or operational control rod management for pressurized water reactors (PWRs) and small modular reactors (SMRs), as well. Additionally, the eighth-core symmetric shuffle option is introduced to help expedite large-scale optimizations. These new features of the optimizer are tested by performing optimizations starting from a base case of an SMR core model that was developed manually and unrodded. The new fuel inventory (NFI) and loading pattern (LP) search in LWROpt was able to eliminate all of the constraint violations present in the initial base solution. However, independent control rod pattern (CRP) searches for the best several LPs found were not successful in generating CRPs without any constraint violations. This indicates that fully decoupling the fuel loading from the CRP optimization can increase the computational tractability of these calculations but at the expense of effectiveness. To improve on the individual search results, a coupled fuel loading (NFI and LP) and CRP search was performed, which produced a better overall result but still with some small constraint violations, emphasizing the fact that optimizing the fuel loading arrangement in a small high-leakage unborated core while concurrently determining its operational rod patterns for a 4-year operational cycle is no easy feat even to an experienced core designer; thus, this process can be greatly aided by employing automated combinatorial optimization tools.

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References

Figures

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Fig. 1

Locations of the CR regions of influence

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Fig. 2

Diagram of the core assembly layout with dimensions and a blowup to show the node structure used in NESTLE

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Fig. 3

Baseline design LP

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Fig. 4

CR bank and group locations

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Fig. 5

Best LP found by LWROpt using only the LP optimization

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Fig. 6

Constraint values as a function of burnup for the best LP/CRP for the individual searches case (constraint limits shown with horizontal lines)

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Fig. 7

CRPs generated for the best LP/CRP for the separate searches case (notches withdrawn, 40 total notches) for each burnup step (kWd/kg)

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Fig. 8

Best LP found by LWROpt using the coupled LP/CRP optimization

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Fig. 9

Constraint values as a function of burnup for the best LP/CRP for the coupled searches (constraint limits shown with horizontal lines)

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Fig. 10

CRPs generated for the coupled LP/CRP search (notches withdrawn, 40 total notches) for each burnup step (kWd/kg)

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